Method and apparatus for connection context aware radio communication management with predictive mobile path

ABSTRACT

An information handling system includes a wireless adapter for communicating with a wireless link and a storage device for storing a spatial-temporal user profile comprising wireless device usage trend data for a location where the information handling system is operating. The information handling system further includes positional detector and an application processor that determines a trajectory estimation during a future time interval. The application processor correlates the wireless device usage trend date for a location in or near the trajectory estimation.

CROSS REFERENCE TO RELATED APPLICATIONS

This application is a continuation of U.S. patent application Ser. No.14/099,686, entitled “Method and Apparatus for Connection Context AwareRadio Communication Management with Predictive Mobile Path,” filed onDec. 6, 2013, and soon to issue, which is a continuation-in-part of U.S.patent application Ser. No. 13/604,906, entitled “Method and Apparatusfor Connection Context Aware Radio Communication Management,” filed onSep. 6, 2012, the disclosures of which are hereby expressly incorporatedby reference in their entirety.

Related subject matter is contained in the following co-pendingapplications:

U.S. application Ser. No. 14/099,698, filed Dec. 6, 2013, entitled“Method and Apparatus for Predicting Mobile Device Wireless Link Qualityof Service Requirements Along a Predicted Path,” invented by Will A.Egner et al., and assigned to the assignee hereof.

U.S. application Ser. No. 14/099,715, filed Dec. 6, 2013, entitled“Method and Apparatus for Determining Optimized Wireless Link Selectionfor a Mobile Device Along a Predicted Path,” invented by Will A. Egneret al., and assigned to the assignee hereof.

FIELD OF THE DISCLOSURE

The present disclosure generally relates to a method and apparatus for aradio resources communication management system to adapt to context andusage of communication channels.

BACKGROUND

As the value and use of information continues to increase, individualsand businesses seek additional ways to process and store information.One option is an information handling system. An information handlingsystem generally processes, compiles, stores, or communicatesinformation or data for business, personal, or other purposes.Technology and information handling needs and requirements can varybetween different applications. Thus information handling systems canalso vary regarding what information is handled, how the information ishandled, how much information is processed, stored, or communicated, andhow quickly and efficiently the information can be processed, stored, orcommunicated. The variations in information handling systems allowinformation handling systems to be general or configured for a specificuser or specific use such as financial transaction processing, airlinereservations, enterprise data storage, or global communications. Inaddition, information handling systems can include a variety of hardwareand software resources that can be configured to process, store, andcommunicate information and can include one or more computer systems,graphics interface systems, data storage systems, and networkingsystems. Information handling systems can also implement variousvirtualized architectures. Data communications among informationhandling systems may be via networks that are wired, wireless, opticalor some combination.

BRIEF DESCRIPTION OF THE DRAWINGS

It will be appreciated that for simplicity and clarity of illustration,elements illustrated in the Figures are not necessarily drawn to scale.For example, the dimensions of some elements may be exaggerated relativeto other elements. Embodiments incorporating teachings of the presentdisclosure are shown and described with respect to the drawings herein,in which:

FIG. 1 is a block diagram of a network environment offering severalcommunication protocol options according to an embodiment of the presentdisclosure;

FIG. 2 is a flow diagram illustrating a method of connecting to awireless network using a context aware radio resource management systemaccording to an embodiment of the present disclosure;

FIG. 3 is a flow diagram illustrating a method of mobile informationhandling system usage profiling according to an embodiment of thepresent disclosure;

FIG. 4 is a chart illustrating an example usage profile of a mobileinformation handling system according to an embodiment of the presentdisclosure;

FIG. 5 is a flow diagram illustrating a method for wireless link trafficreporting according to an embodiment of the present disclosure;

FIG. 6 is a flow diagram illustrating a method for wireless link energyconsumption reporting according to an embodiment of the presentdisclosure;

FIG. 7 is a flow diagram illustrating a method of establishing optimizedwireless link selection for a mobile device along a predicted path;

FIG. 8 is a flow diagram illustrating an example method for predictingfuture mobile device path locations;

FIG. 9A is an example embodiment of a bin map for locations of apredicted path in a user area;

FIG. 9B is an example embodiment of a bin map for a history ofvisitation to locations in a user area;

FIG. 9C is an example embodiment of a bin map for predicted QoS for avariety of wireless links at locations in a user area;

FIG. 10 is a flow diagram illustrating a method for determining mobiledevice wireless requirements along a path for a mobile device;

FIG. 11 is another example flow diagram illustrating a method fordetermining mobile device wireless requirements along a path for amobile device;

FIG. 12 is a flow diagram illustrating a method for estimating wirelesslink QoS levels along a predicted path;

FIG. 13 is another example flow diagram illustrating a method forestimating wireless link QoS levels along a predicted path; and

FIG. 14 is a block diagram illustrating an information handling systemaccording to an embodiment of the present disclosure.

The use of the same reference symbols in different drawings indicatessimilar or identical items.

DETAILED DESCRIPTION OF THE DRAWINGS

The following description in combination with the Figures is provided toassist in understanding the teachings disclosed herein. The descriptionis focused on specific implementations and embodiments of the teachings,and is provided to assist in describing the teachings. This focus shouldnot be interpreted as a limitation on the scope or applicability of theteachings.

FIG. 1 illustrates a network 100 that can include one or moreinformation handling systems. For purposes of this disclosure, theinformation handling system may include any instrumentality or aggregateof instrumentalities operable to compute, classify, process, transmit,receive, retrieve, originate, switch, store, display, manifest, detect,record, reproduce, handle, or utilize any form of information,intelligence, or data for business, scientific, control, entertainment,or other purposes. For example, an information handling system may be apersonal computer, a PDA, a mobile information handling system, aconsumer electronic device, a network server or storage device, a switchrouter or other network communication device, or any other suitabledevice and may vary in size, shape, performance, functionality, andprice. The information handling system may include memory, one or moreprocessing resources such as a central processing unit (CPU) or hardwareor software control logic, and operates to execute code. Additionalcomponents of the information handling system may include one or morestorage devices that can store code, one or more communications portsfor communicating with external devices as well as various input andoutput (I/O) devices, such as a keyboard, a mouse, and a video display.The information handling system may also include one or more busesoperable to transmit communications between the various hardwarecomponents.

In a particular embodiment, network 100 includes networked mobileinformation handling systems 110, 120, and 130, wireless network accesspoints, and multiple wireless connection link options. Systems 110, 120,and 130 represent a variety of computing resources of network 100including client mobile information handling systems, data processingservers, network storage devices, local and wide area networks, or otherresources as needed or desired. As specifically depicted, systems 110,120, and 130 may be a laptop computer, tablet computer, or smartphonedevice. These user mobile information handling systems 110, 120, and130, may access a wireless local area network 140, or they may access amacro-cellular network 150. For example, the wireless local area network140 may be the wireless local area network (WLAN), a wireless personalarea network (WPAN), or a wireless wide area network (WWAN). Since WPANor Wi-Fi Direct Connection 148 and WWAN networks can functionallyoperate similar to WLANs, they may be considered as wireless local areanetworks (WLANs) for purposes herein. Components of a WLAN may beconnected by wireline or Ethernet connections to a wider externalnetwork. For example, wireless network access points 145 may beconnected to a wireless network controller and an Ethernet switch.Wireless communications across wireless local area network 140 may bevia standard protocols such as IEEE 802.11 Wi-Fi, IEEE 802.11 ad WiGig,IEEE 802.15 WPAN or similar wireless network protocols. Alternatively,other available wireless links within network 100 may includemacro-cellular connections 150 via one or more service providers 160 and170. Service provider macro-cellular connections may include 2Gstandards such as GSM, 2.5G standards such as GSM EDGE and GPRS, 3Gstandards such as W-CDMA/UMTS and CDMA 2000, or 4G standards such asWiMAX, LTE, and LTE Advanced.

The voice and packet core network 180 may contain externally accessiblecomputing resources and connect to a remote data center 186. The voiceand packet core network 180 may contain multiple intermediate webservers or other locations with accessible data (not shown). Connection182 between the wireless network 140 and remote data center 186 may bevia Ethernet or another similar connection to the world-wide-web, a WAN,a LAN, another WLAN, or other network structure. Such a connection 182via WLAN access point/Ethernet switch 145 to the external network is abackhaul connection. The access point 145 may be connected to one ormore wireless access points in the WLAN before connecting directly to amobile information handling system or may connect directly to one ormore mobile information handling systems 110, 120, and 130.Alternatively, mobile information handling systems 110, 120, and 130 mayconnect to the external network via base station locations at serviceproviders such as 160 and 170. These service provider locations may benetwork connected via backhaul connectivity through the voice and packetcore network 180.

Remote data center 186 may include web servers or resources within acloud environment. For example, remote data centers can includeadditional information handling systems, data processing servers,network storage devices, local and wide area networks, or otherresources as needed or desired. Having such remote capabilities maypermit fewer resources to be maintained at the client mobile informationhandling systems 110, 120, and 130 allowing streamlining and efficiencywithin those devices. Similarly, remote data center 186 permits fewerresources to be maintained in other parts of network 100.

In an example embodiment, the cloud or remote data center 186 may runhosted applications for systems 110, 120, and 130. This may occur byestablishing a virtual machine application executing software to manageapplications hosted at the remote data center 186. Mobile informationhandling systems 110, 120, and 130 are adapted to run one or moreapplications locally, and to have hosted applications run in associationwith the local applications at remote data center 186. The virtualmachine application may serve one or more applications to each of usermobile information handling systems 110, 120, and 130. Thus, asillustrated, systems 110, 120, and 130 may be running applicationslocally while requesting data objects related to those applications fromthe remote data center 186 via wireless network. For example, anelectronic mail client application may run locally at system 110. Theelectronic mail client application may be associated with a hostapplication that represents an electronic mail server. In anotherexample, a data storage client application such as Microsoft Sharepointmay run on system 120. It may be associated with a host applicationrunning at remote data center 186 that represents a Sharepoint datastorage server. In a further example, a web browser application may beoperating at system 130. The web browser application may request webdata from a host application that represents a hosted website andassociated applications running at remote data center 186.

To communicate within the network 100, the systems 110, 120, and 130each have a wireless interface module or wireless adapter, hereinafterreferred to as a wireless adapter. System 110 includes a wirelessadapter, system 120 includes a wireless adapter, and system 130 includesa wireless adapter. The wireless adapters are operable to provide awireless radio frequency interface 115, 125, and 135 to transmit andreceive voice and data between the respective systems 110, 120, and 130and one or more external networks via wireless network 140 or 150.

Although 115, 125, and 135 are shown connecting wireless adapters towireless networks 140 or 150, actual wireless communication may linkthrough a wireless access point 145 or a service provider tower such asthat shown with service provider A 160 or service provider B 170. Awireless link may also be made between the wireless adapter and anothermobile information handling system in a WPAN or Wi-Fi Direct Connection148. Since one aspect of the disclosed embodiments involves selection ofwireless links by a context aware radio resource management system, noparticular wireless link selection is depicted in FIG. 1.

The wireless adapters can represent add-in cards, wireless networkinterface modules that are integrated with a main board of respectivesystems 110, 120, and 130 or integrated with another wireless networkinterface capability, or any combination thereof. In an embodiment thewireless adapters may include one or more radio frequency subsystemsincluding transmitters and wireless controllers for connecting via amultitude of wireless links. In an example embodiment, a mobileinformation handling system may have a transmitter for Wi-Fi or WiGigconnectivity and one or more transmitters for macro-cellularcommunication. The radio frequency subsystems include wirelesscontrollers to manage authentication, connectivity, communications,power levels for transmission, buffering, error correction, basebandprocessing, and other functions of the wireless adapters.

The radio frequency subsystems of the wireless adapters may measurevarious metrics relating to wireless communication. For example, thewireless controller of a radio frequency subsystem may manage detectingand measuring received signal strength levels, bit error rates, signalto noise ratios and other metrics relating to signal quality andstrength. In one embodiment, a wireless controller may manage one ormore radio frequency subsystems within a wireless adapter. The wirelesscontroller also manages transmission power levels which directly affectradio frequency subsystem power consumption. To detect and measure powerconsumption by a radio frequency subsystem, the radio frequencysubsystem may implement current and voltage measurements of power thatis directed to operate a radio frequency subsystem. The voltage andcurrent provides power measurement in milliwatts. Energy consumed may becalculated from sample measurements by taking average power measuredover a duration of transmission. In an alternative embodiment of powermeasurement, counter registers may be used to estimate power consumedduring transmissions. Energy measurement may be a sampled during a countcycle. In this case, a sample energy measurement per count is multipliedinto a count for operation of a radio subsystem. In this way, powerconsumption may be estimated.

The wireless adapters may be capable of connecting via a WLAN 140 or amacro-cellular network (WWAN) 150 and service provider 160 or 170 in avariety of the wireless standards as described above. Each of thewireless adapters for client mobile information handling systems 110,120, and 130 are uniquely identified on network 100 via one or moreunique identifiers permitting authentication and access. For example,the wireless device can each be identified by one or more SubscriberIdentity Modules (SIM), one or more of a media access control (MAC)address, an Internet protocol (IP) address, a world wide name (WWN), oranother unique identifier such as a user name and password, as needed ordesired. Association of a user and a wireless interface module of a userinformation handling system may be made via communications across anetworking control plane. For example, a user information handlingsystem may be associated with a user via communication with a databasesuch as Home Subscriber Server (HSS), Active Directory or similardatabase. This database may reside in the voice and packet core network180, at a base station at 160 or 170, or elsewhere in the externalnetwork.

The wireless adapters may operate in accordance with any wireless datacommunication standards. To communicate with wireless local area network140, standards including IEEE 802.11 WLAN standards, IEEE 802.15 WPANstandards, WWAN such as 3GPP or 3GPP2, or similar wireless standards maybe used. The wireless LAN network 140 may provide connectivity via Wi-Fior WiGig for example. The wireless network 140 may have a wireless mesharchitecture in accordance with mesh networks described by the abovewireless data communications standards or similar standards. Wirelesslinks 115, 125, and 135 may also connect to the external network via aWPAN, WLAN or similar wireless switched Ethernet connection. Thewireless data communication standards set forth protocols forcommunications and routing via access point 145, as well as protocolsfor a variety of other operations. Other operations may include handoffof client devices moving between nodes, self-organizing of routingoperations, or self-healing architectures in case of interruption.

Wireless links 115, 125, and 135 may connect to a macro-cellularwireless network 150 via one of the service providers 160 or 170. In thedepicted example, service provider A 160 may provide wireless dataconnectivity via a 3G or 4G protocol. Service provider B 170 may offerconnectivity via a 2.5G, 3G or 4G protocol. Any combination ofmacro-cellular wireless connectivity is possible for each or both of theservice providers. The connection quality of service (QOS) and speed ofwireless links 115, 125, and 135 may vary widely depending on severalfactors including the service provider bandwidth, the number of mobileinformation handling systems and users in a location, and other factors.Quality of service impacts energy consumption and efficiency of a mobileinformation handling system communicating wirelessly. Thus, selection ofa wireless link may depend on assessment of the link radio frequencyconditions. Radio frequency conditions for wireless links will evolveover time. Differences in wireless link QOS or efficiency will also varyminute-by-minute, hourly, daily, weekly or monthly or during even longerperiods. Thus, assessment may need to be regular.

Wireless link conditions will vary depending on the type of servicelikely to be requested by the mobile information handling system. Forexample, voice communication may be most efficient on a 2G wirelessprotocol. Voice communication on 4G may be more costly in terms of timerequired for authentication and connectivity negotiation or in terms oftransmission power requirements. Data services relating to messaging andSMTP email may have the lowest power cost on 2.5G protocols due to thesimplest access barriers there. Higher level data services requiringgreater wireless bandwidth may more efficiently use recently implementedprotocols. For example, audio streaming may be optimal for 3G protocols.Video streaming and HTTP web browsing may be best suited to 4G protocolsand much less efficient at lower protocols which are not designed toaccommodate large data throughput.

As the protocols become more advanced, additional registration andinitialization for data becomes costly from a processing and powerconsumption standpoint. This is balanced against the capabilities of themore advanced protocols to handle data transfers. More complicatedcommunication protocols result in greater processing time andauthentication/connection message exchange. More robust processor orcontroller operation and longer delays for transmitter or receivercircuits consume power. On the other hand, certain protocol advancementsare designed to make data transfers quicker and more efficient. Thus forexample, the 4G protocol may generally consume more power duringoperation than 2.5G for voice communications, but less power for highvolume data transfers.

For this reason, the mobile information handling system operatingcontext can play an important role in determining wireless linkconditions and efficiency from a power consumption standpoint.Information about wireless link connection quality and capacity for aservice to be used can be advantageous in optimizing communicationchannel selection. In most cases, transmission or reception via amacro-cellular network 150 base station at a service provider 160 or 170will take more power than communication via WLAN such as Wi-Fi. Amongmacro-cellular systems, energy consumption generally, but not in allcircumstances, increases at each advancement of technology protocol from2G to 4G. Plus, increased traffic levels on an advanced macro-cellularprotocol may slow down in comparison to an older technology with lessactive traffic. Additional future macro-cellular protocols arecontemplated as well. Those protocols may require additional energydemands of mobile information handling systems.

Factors impacting energy consumption include switching and signalingduring communication access, setup, and authentication. Additionalfactors that impact energy consumption include control communications,latencies, transmission/reception, and switching for the wireless link.As described above, these factors can be specific to the type ofwireless service being requested, whether voice, messaging, SMTP, Audio,Video, HTTP or other service types. It can also be specific to themobile information handling system used. Certain protocols may not beavailable on some mobile information handling systems. In each instance,radio frequency transmission subsystems and controllers operate andconsume device power. Based on these numerous factors, the system of thepresent embodiment may automatically switch between radio networktechnologies or service providers to optimize radio frequencyconditions, traffic conditions, device power consumption, cost, or anyof the above. Selection of a wireless service provider and technologyprotocol may generally depend on the optimal wireless technology usedfor a service requested, the radio frequency conditions of a link,traffic conditions for the wireless link, and availability of a link.

Information handling systems 110, 120, and 130 may connect to thenetwork 140 or 150 via an initial default wireless link with one of theservice providers 160, 170 or via a WPAN, Wi-Fi, or WiGig connection.The default wireless link allows the mobile information handling systems110, 120, and 130 to communicate with the network and in particular witha network broker server system 190. The network broker server system 190and/or mobile information handling systems 110, 120, and 130 leverageinformation from a Wireless Intelligence Report system database 195 andmay control access to a macro-cellular service provider or WLAN. Networkbroker server system 190 may be operated as a mobile virtual networkoperator (MVNO), a wireless service provider wholesaler, a mobilenetwork operator (MNO), or similar type of network broker. The networkbroker server system 190 may have contractual bulk access to networkservices from a variety of mobile network operators or serviceproviders. With this access to network services from multiple serviceproviders, the network broker server system 190 may enable access orswitch access for information handling systems 110, 120, and 130 amongthe available service providers. For example, network broker 190 mayselect among service providers 160 and 170 to information handlingsystems 110, 120, or 130. Information handling systems 110, 120, and 130may be multiband capable via the wireless adapters therein. Antennasystem frequency and radio protocols for a service provider may beadjusted by way of software programming of transmitter/receiver systemsof the wireless adapters in mobile information handling systems 110,120, and 130. Information handling systems 110, 120, and 130 may bemultiband capable via these tunable antennas enabling a wireless adapterto target specific bands depending on the selected service provider andwireless protocol.

The network broker server system may also access aggregated WirelessIntelligence Report 195 about the performance of service providers 160or 170 and the various wireless protocols they have made available. Theaggregated Wireless Intelligence Reports 195 may be accumulated or crowdsourced from multiple handsets operating on a given network or networks.This feature will be described further below. In an alternativeembodiment, the aggregated Wireless Intelligence Report 195 may bestored on the network broker server system itself. The selection of aservice provider and protocol by the network broker server system 190for an information handling system seeking a wireless link will beaccording to a recommendation received from a context aware radioresource management system agent running on the information handlingsystem. The wireless link recommendation may be a weighted list ofservice provider options and protocols. It may be submitted by thecontext aware radio resource management system operating to the networkbroker server system 190 in the described embodiment. Alternatively, thecontext aware radio resource management system agent could run remotelyon the network broker server systems or at a remote data center and usea default wireless link until an optimal wireless link is selected andthe system is switched.

In an alternative embodiment, the radio frequency subsystems of awireless adapter may contain individual subscriber identity module (SIM)profiles for each technology service provider and their availableprotocol. These multiple SIM profiles on the mobile information handlingsystem may be provided by one broker such as an MVNO, or by multipleservice providers. The system may have an application processor for thewireless adapter capable of switching between SIM profiles at theinformation handling system. The switching between SIM profiles andaccessing the service providers may be conducted by information handlingsystems 110, 120, or 130. Thus, a wireless link recommendation from acontext aware radio resource management system would not need to betransmitted to network broker server system 190. Information handlingsystems 110, 120, or 130 may select a SIM profile for a recommendedservice provider and protocol and seek direct access. Nonetheless,billing and other coordination of SIM profile options may be managed bya broker such as an MVNO. The context aware radio resource managementsystem is described further below.

FIG. 2 illustrates a context aware radio resource management method foruse in selecting a network and technology within wireless network 100 ata given location. Several factors are assessed by the context awareradio resource management method in selecting a radio technology and aservice provider. A software agent is deployed at a mobile informationhandling system or elsewhere in the network for executing the contextaware radio resource management method. At step 210, the context awareradio resource management system software agent obtains user profiledata. The user profile data establishes an approximate cyclostationaryusage pattern of the mobile information handling system. The time ofday, location, types of usage, and usage percentages during a sampletime interval are example factors included in the user profile data.This user profile data also may include a confidence of the estimate.This may be a statistical measurement of a mean and standard deviationfor a set of data. Alternatively, the confidence of estimate may involvea goodness of fit metric to an expected set of values. Alternativestatistical analysis may be performed on the user profile data toprovide a confidence of the estimate.

At step 220, the context aware radio resource management system receiveswireless link radio frequency broadband traffic reports. For locationand time, available radio technologies and service providers are listed.The reports contain data relating to location, time and a radiofrequency profile of given radio technologies for the available serviceproviders. The data may also include an associated confidence ofestimate. The wireless link radio frequency profile may combine recentreports, historical traffic reports, as well as data measured via anactive device radio frequency scan. In order to minimize a mobileinformation handling system battery power consumed, radio frequencybroadband traffic reports from the network may only be requested or sentwhen a service provider network or a mobile information handling systemdetects a significant change in signal quality or the network brokerserver detects that the local crowd source information is out of date.

The context aware radio resource management system receives batterypower level data at step 230 from an intelligent battery managementsystem of the mobile information handling system. The battery powerlevel input may determine that certain wireless communication protocolsare too costly in terms of power. Below a defined battery levelthreshold, the context aware radio resource management system maydisable the most advanced protocols to save energy. For example, withonly 10% battery power remaining, the context aware system may recommendto a user to disable high power consuming protocols such as 4G. Theoption may be given to the user, or automatic shut down of the radiofrequency subsystem may take place. In a further example, the contextaware system may recommend or shut down 3.5G at 5% remaining batterypower. Any threshold levels may be set to trigger recommended shut down.This data provides the context aware radio resource management systemwith an ability to manage the mobile information handling system powerconsumption when battery levels are low. The context aware radioresource management system may switch wireless protocols being whenreceiving a shut down recommendation. The switching may happen with acontinuous connection to the same service provider.

The intelligent battery power management may also determine whichservices or protocols are unavailable at a given location. Thisinformation may come in part from radio frequency profile data in theradio frequency broadband traffic reports. In that case, the radiofrequency subsystem transmitters, receivers, and controllers associatedwith unavailable protocols may be turned off by the context aware radioresource management system. For example, if no 4G WWAN is detected, theradios capable of communicating with these protocols may be turned offin the mobile information handling system. As before, the option may berecommended to the user of the mobile information handling system beforeshutting a subsystem down.

Step 240 depicts that a variation of the mobile broadband trafficreports may be used by the context aware radio resource managementsystem. The variation is a link energy consumption report. These energylink reports contain data relating to time, location and radio frequencyprofile information similar to the radio frequency broadband trafficreports 220. In addition, measurements of energy consumed during use ofa specified wireless link for a specified wireless service type isreported. The energy link data profile matrix can provide more detailedinformation above the mobile broadband radio frequency traffic reports.As with other input factors, a confidence of estimate associated withthis data may be included. The energy link report data may combinerecent energy link profiles, historical energy link reports, andmeasurements through mobile information handling system scans duringoperation.

At method step 250, the context aware radio resource management systemreceives the user profile data 210, the wireless link radio frequencybroadband traffic reports 220, and battery power level data 230.Alternatively, the energy link reports 240 may be received as avariation of the wireless link radio frequency broadband traffic reports220. These inputs are assessed by the context aware radio resourcemanagement system software agent at 250. The context aware radioresource management system software agent determines the optimal radiofrequency technology protocol and service provider to be used. Thisdetermination is based, at least in part, on some subset of data in theinput reports. Also, the settings such as what protocols are available,which protocols have been shut down, or what power is required totransmit on a given protocol are determined for the mobile informationhandling system.

In one embodiment, the wireless link assessment 250 may result in aranked list of service providers. Using user profile reports 210 andradio frequency link reports 220, each service provider may be given anoverall rank as follows:Service Provider Rating(j)=Σ_(i−1 to k)(User Profile by Technology*LinkRating),

-   -   where i=a technology index, j=service provider index, and k=the        number of wireless technologies.

The service providers can be ranked by this score. For a matrix of linkprotocols=[2G, 2.5G, 3G, 3.5G, 4G], an example user profile bytechnology may result in the following matrix (30%, 25%, 15%, 30%, 0%).The user profile shows the anticipated protocol usage score from alocation and time period. A Link Rating (j) may result in the followingmatrix (70%, 80%, 95%, 90%, 30%). The link rating shows a quality ofservice score by protocol for a service provider at a location and time.The service provider rating for a user profile in this example wouldresult in 0.8225. Altering the weight of factors may increase ordecrease the relevance of certain protocols depending on the change tothe calculations. Either the user profile scores or the link ratings maychange the calculations of the scores assigned there. This is describedfurther below. The above values serve only as an example.

Battery power levels 230, energy link reports 240, and additionalfactors, such as subscriber cost of wireless link usage, may also beassessed to select a wireless link. Subscriber cost or settings mayinfluence the determination by weighting protocol options and influencethe scoring described below. Alternatively, settings or subscriber costmay be used to mask out protocol options altogether.

The selection of a wireless link by the context aware radio resourcemanagement system may depend on the factors and settings describedabove. For example, if optimal speed of connection is the goal with lessconsideration of power consumption, the weight assigned by the contextaware system to input data may be influenced. This may be the case ifthe context aware resource management system detects a connection to anAC power source. User profile data 210 showing usage and the wirelesslink radio frequency broadband traffic reports 220 indicating linkquality and capacity will be more heavily weighted. Energy consumptiondata may be less heavily weighed. If on the other hand, lower powerconsumption and long battery life are optimal considerations, batterypower level data 230 and the energy link reports 240 may be more heavilyweighted. Any combination of weighting involving anticipated usage,radio frequency channel quality, battery power levels, or efficientpower consumption may be used in the present embodiment.

Upon determination of an optimal link or links, the context aware radioresource management system provides a command to select a preferredwireless link protocol and service provider. In an alternativeembodiment, a list is created providing a preferred set of wirelesslinks and protocols. The context aware radio resource management systemmay also list wireless links in rank order as described above.

At method step 260, a request is made for access to the selectednetwork. The context aware radio resource management system transmits acommand or a list of selected wireless link providers and protocols to anetwork broker server. The mobile information handling system contactsthe network broker server via a default wireless link made available toit. With the weighted list, the network broker server may negotiateaccess to preferred service providers and protocols for the location ofthe mobile information handling system. Alternatively, the context awareradio resource management system provides a list or command to anapplication processor controlling SIM profile selection within themobile information handling system. Then the wireless adapter negotiatesaccess to a preferred service provider and selects a protocol.

At step 270, if the access request is accepted by the service provider,the mobile information handling system is connected to the selectedservice provider and wireless protocol. If access is declined, thenetwork broker server or wireless adapter will request access to anotherpreferred protocol and service provider in the weighted list receivedfrom the context aware radio resource management system. If the list isin rank order, then one embodiment may turn to the next ranked protocoland service provider. This repeats until a satisfactory wireless link isfound and access made for the mobile information handling system.

FIG. 3 illustrates a method 300 for generating an end-user profile inthe context aware radio resource management system. In the first step310, the context aware radio resource management system software agentis started to optimize device performance in selecting a wireless link.At step 320, the context aware radio resource management system softwareagent initiates a baseline device profile state. The device profilestate reflects expected usage for the mobile information handlingsystem. It includes various usage service types. Example usage types mayinclude voice, audio streaming, video streaming, internet usage, emailcommunication, SMS or other messaging. A previous user data profilecollected for the operation of the mobile information handling systemmay serve as the baseline device profile. Such a profile is specific tothe location of the device and to a time slice during which operation isbeing optimized. Locations may be assigned to geographic zones such as acampus, city, borough, county, etc. Time may be assigned to defined timeperiods during a day but may differ across days of the week. This zoningand time definition is optional but will help control the number ofdifferent user profiles generated.

In one embodiment, a set default user profile may be used as a baseline.For example, the client service profile may assume SMS messagingconsumes 10% of device usage, voice communications consume 30%, videostreaming consumes 10% of usage, audio streaming consumesl5% of usage,SMTP email consumes 10%, and internet activity consumes 25%. Thisbaseline state may be specific to the mobile information handling systemtype. For example, the mobile information handling system may be gearedtoward usage on a certain network protocol. For example, certain systemsmay be optimized to operate on a 3G or 4G network. Additionally, adefault service provider and wireless protocol may generally be assignedto the mobile information handling system. This default wireless linkmay affect or set the baseline profile state.

At step 330, the context aware radio resource management system mayinitiate operational measurements according to time of day, location ofmobile information handling system, and usage levels for various usagetypes. The usage data measurements may be taken during sample intervals.For example, during a time period from a specific location zone, thecontext aware radio resource management system may monitor operation ofthe mobile information handling system. It will measure the dwell timeor use percentage of each type of service. This can include measuringminutes used or number of calls made for voice service. It can measurebytes transferred or number of requests made for video streaming oraudio streaming. It may measure the number of messages sent and receivedor bytes transferred for SMTP, SMS, or similar messaging. The contextaware radio resource management system can also measure the datarequests and responses or data volumes exchanged in internet accesses.At each sample interval, the available service providers and availablewireless link protocols may be determined as well.

The results of the measurements are incorporated into a user profile atstep 330. Rather than strictly relying of total data volumes or numberof requests, the measurements may be scaled or normalized to reflect apercentage of service usage. This normalized scoring permits comparison.The normalization may be scaled to permit scores of usage reflectingimportance or frequency of access to the service types. For example,while audio/video streaming may take a large amount of data, usage maybe uncommon. For the same time period, the voice service usage or SMTPmessaging may be substantially more frequent but may not transfer asmuch data volume. Therefore, service recommendations may be betterscaled toward frequency of accesses rather than total data throughputvolumes. If on the other hand video streaming is a daily occurrence,even if only one request occurs at that time period, then scaling maylean toward total data volume. In this case, normalization scaling infavor of data throughput volume may more accurately reflect the usage.

The use or usage percentage may be measured and scored according to thepreferred parameters set in the context aware radio resource managementsystem. It may also be averaged with the baseline default or historicaluser profile state if so desired. For example, previously measured usagedata for a location zone and time period may provide higher dataconfidence if averaged into measured data.

Measurements may be repeatedly taken in later sample intervals at step340. Such measurements may be conducted throughout an entire day andover the course of several days or longer. The multiple samplemeasurements of the mobile information handling system usage comprise aspatial-temporal user profile. The spatial-temporal user profile mayhave an associated confidence estimate. At step 350, thespatial-temporal user profile and any confidence estimate will be storedeither at the mobile information handling system or elsewhere in anavailable database. The spatial-temporal user profile for the mobileinformation handling system usage assists in selection of radiofrequency links for given times and location zones. The user profile maypredict the predominantly used combination of services typical of themobile information handling system during a time period or from acertain location. The predicted service usage assists in selecting anoptimal service provider and radio frequency protocol. Thespatial-temporal user profile information will be stored in the mobileinformation handling system to protect end-user privacy information

To apply this data to selection of a wireless service provider andprotocol, the usage percentage levels are mapped to service protocolsavailable to a mobile information handling system. The mapping of usepercentages to a protocol may involve assigning the use percentage for aservice to the lowest power consuming protocol available for a usagetype. In other words, the service type usage score is mapped to thetechnology protocol most efficient for that service type. For example,voice communication usage may be assigned to a 2G protocol whereas audioor video streaming may be assigned to 4G. These energy efficiency rulesare stored as part of system parameters. These parameters are used tomap services to optimal wireless technology. The parameters may also beadjusted as a function of energy state or battery power levels of themobile information handling system. The parameters may also be specificto the make or model of the mobile information handling system and itscapabilities in processing, memory, radio frequency transmission systemsand other features.

Once the usage levels are measured and scaled according to anticipatedimportance of data throughput versus frequency of access, the result mayscore messaging at 20% of usage, voice at 30% of usage, video at 10% ofusage, audio at 15% of usage, SMTP at 5% of usage, and internet at 20%of usage. For optimizing minimal power consumption, each service usageis mapped to a service protocol. For example, voice may consume theleast power on a 2G network. If 2G cannot accommodate video streaming,it may be eliminated however. The voice score is associated with themost efficient choice available. If video streaming is very infrequentat less than 5%, then elimination of 2G protocol may be disregarded.Should the rare video streaming service request occur, the cost ofswitching protocols may be worthwhile at that time. Switching protocolsmay even occur within one service provider to minimize cost of access,negotiation, authentication, and switching with a different serviceprovider.

In the present example, messaging and SMTP email are optimal at 2.5G.The email usage score is then mapped to 2.5G. 3G may consume more power,but also may be determined to provide audio streaming services mostefficiently. Thus, the audio streaming usage score is mapped to 3G.Internet access and video streaming may be most efficient in a 4Gprotocol and thus mapped to this protocol. If 4G is unavailable, then3.5G may be selected instead if it is the next most efficient protocollevel.

The mapping will result in a service profile of protocol technologyassigned according to optimal power consumption efficiency for theservices anticipated for a mobile information handling system. Forexample, 2G may be weighted with a value of 30% as optimal for voiceusage. 2.5 G may be weighted at 25% as optimal for SMS messaging andSMTP email messaging. 3G may be weighted at 15% as optimal for audiostreaming usage. And 3.5G may be weighted at 30% for video streaming andhttp internet access in the case that 4G is unavailable. For a matrix oflink protocols=[2G, 2.5G, 3G, 3.5G, 4G], a user profile by technologymay result in the following example matrix (30%, 25%, 15%, 30%, 0%).This spatial-temporal user profile data is then utilized by the contextaware radio resource management system alone or in combination withother profile reports shown in FIG. 2 to select a wireless link.

FIG. 4 illustrates a graphical example of spatial-temporal user trendsfor a mobile information handling system. As shown in FIG. 4, user trendbehavior measurements are shown as a function of time and location. Fiveusage types are illustrated in this example, voice, video streaming,audio streaming, email, and internet usage. Usage amounts are shownalong the x-axis. The y-axis depicts time and various locations. In thisexample, three locations and time periods are defined, though more orfewer could exist. Those time periods are early morning usage atLocation 1, business hours usage at Location 2, and after work hours atLocation 3. Each general time period may be comprised of multiple timeslices with separate data samples. The mobile information handlingsystem may apply a curve fitting approach to the user profile data tocompress information associated with a level of use per type of serviceper unit of time. An n-order polynomial approach may be used to reduceinformation to N parameters.

Email usage is depicted in trace 410. Voice bandwidth usage is depictedin trace 420. Internet usage is depicted in trace 430. Audio streamingusage is depicted in trace 440. And video streaming usage is depicted intrace 450. In many cases, the user profile data can be expected to becyclostationary. In other words, the usage trends repeat themselves. Forexample, usage may repeat itself daily during a business week. In theexample of FIG. 4, voice bandwidth usage 420 increases mid-day duringbusiness hours at location 2 during lunch. Voice bandwidth consumption420 will again increase during after work hours at location 3. This mayinclude increasing during a commute home or upon returning home.Similarly, trends in email usage 410 may show peaks at all threelocations with lower bandwidth usage trends arising during non-breakbusiness hours at location 2 and late in the evening after work atlocation 3. Thus, despite variability in these usage schedules, somecyclostationary consistency can be established. For this reason, timeperiod data may be averaged for weekdays or may be specific toWednesdays depending on the trends. Variability may be accounted forwith confidence estimates on the data.

FIG. 5 shows a method 500 for establishing a mobile broadband trafficreport for a wireless link for wireless links. The mobile broadbandtraffic report partially comprises a spatial-temporal radio frequencyprofile for the wireless links. The systems begins with a baselinemobile broadband report available from a network broker system oravailable from cooperative service providers if no previously measureddata is available. By way of example, baseline data may be drawn fromavailable wireless coverage maps.

Key performance indicators (KPI) comprise a spatial-temporal radiofrequency profile. Data such as received signal strength (RSSI),signal-to-noise ratios (SNR), or signal to interference ratios (SIR) maybe relevant channel quality indicators in a KPI matrix. Other data, mayinclude data throughput speeds and communication latencies. One or moreof these performance indicators may be used to compute a link rating fora wireless link. Baseline reports rely on estimated values. For exampleusing baseline estimated received signal strength indicators (RSSI), alink rating may be computed as follows:Link Rating(i,j)=MAX(MIN(100%, (Estimated RSSI Signal Carrier−MinimumSignal)/Max RSSI signal−Minimum RSSI signal,0%),where i is a technology index and j is a service provider index.

A maximum RSSI level may be defined in a technology protocol, forexample as −70 dBm. The minimum RSSI level may be defined as well, forexample at −110 dBm. RSSI is not the only key performance indicator thatmay be used to compute link ratings. Link rating may be based ondifferent key performance indicator values besides received signalstrength. Alternatively, multiple key performance indicator values maybe used in the computation of a link rating.

A link rating matrix is established by link protocols for a serviceprovider. For a matrix of [2G, 2.5G, 3G, 3.5G, 4G], the baseline LinkRating (j) computation may result in (70%, 80%, 95%, 90%, 30%). 100%indicates best signal link quality and 0% indicates a signal qualitybelow a minimum acceptable level. The Link Rating (j) evaluates aservice provider overall. The context aware radio resource managementsystem may use the link rating scores to evaluate the optimal wirelessservice providers and available protocols for the anticipated usages.Once a service provider is selected, the context aware radio resourcemanagement system may switch between protocols within one serviceprovider depending on changes in usage. Thus, the link rating protocolmatrix can assist in selecting a service provider with the best scoresin multiple protocols.

At block 510, a context aware radio resource management system operatingon a mobile information handling system may scan for wireless linkmobile broadband traffic reports fitting a time and location zone foroperation. Wireless link mobile broadband traffic reports may beretrieved from a central server database in the wireless networks 140and 150. Alternatively they may be located elsewhere in a database suchas at a network broker server system. The baseline report may besupplemented or superseded by any fresh or historical mobile trafficreports to assist in selecting a service provider and protocol. Recentor historic radio frequency profiles for time period and location zonemay be used to update or supplement the wireless link mobile broadbandtraffic reports. More recent data may be of greater relevance however.For example, the link ratings in a radio frequency profile may utilizerecently measured RSSI values instead of estimated values.

Mobile broadband traffic reports are aggregated via crowd sourcing. Theymay be categorized by location zone and have time and date stamps toidentify freshness. Crowd sourcing of information will enhance theavailability of accurate data for location zones and times of mobileinformation handling system operation. For example, if a mobileinformation handling system makes a request for a fresh mobile broadbandtraffic report, the central server database may have reports from othermobile information handling systems with recent timestamps.Alternatively, the central server database may make a request for arecent mobile broadband traffic report from mobile information handlingsystems in the same location. Whether via recent storage in the centraldatabase or via a recent request of fresh crowd sourced mobile broadbandtraffic reports, such a report may avoid the need for the mobileinformation handling system to conduct a radio frequency scan itself.

Crowd sourcing mobile broadband traffic reports for locations and timesprovides a higher chance that a current mobile broadband traffic reportfor a location is available. It also increases the available data pointsproviding greater certainty and reliability of data. Part of the benefitof crowd sourcing may also involve performing a hysteresis analysis onthe data coming from multiple mobile information handling systems todetermine trends in wireless link selection. When a wireless link isreported having low traffic and good radio frequency conditions, trafficfrom systems using the context aware radio resource management systemwill elect that wireless link. If a large part of the crowd of mobileinformation handling systems begin to pile onto whichever wireless linkis reported to have the best available bandwidth, that link will slowdown and underperform. The mobile broadband traffic reports account forthis by conducting a hysteresis analysis. If a large number of usersbegin to select this wireless link, then the method for generatingmobile broadband traffic reports accounts for this traffic and altersthe recommended wireless links. For example, a second best option may berecommended as optimal for traffic and radio frequency conditionsinstead. Each crowd sourced mobile broadband traffic report identifiesits selected link. A count of these selections can be compared to athreshold rate level of selections for a given link. If the rate ofselections exceeds the threshold for a link, then the recommendation maybe altered.

At block 520, the method determines whether a fresh mobile broadbandtraffic report is available for the location of the mobile informationhandling system. If so, a fresh mobile broadband traffic report isretrieved from a central server database. At 530, the method assessesthe fresh mobile broadband traffic reports and any available historicalmobile broadband traffic reports. Historical mobile broadband trafficreports may be stored locally for the mobile information handling systemor received from a central server database. Assessment of both fresh andhistorical data is used to determine one or more optimal wireless linksat step 530. The combination of fresh and historical informationprovides a radio frequency channel performance assessment of thewireless links. While fresh report data may be weighted more, historicaldata may add additional depth of data. The context aware radio resourcemanagement system elects a wireless link based, at least in part, on theradio frequency channel performance profile as described in FIG. 2.

If no fresh mobile broadband traffic reports are available at step 520,the method seeks stored historical mobile broadband traffic reports fromthe central server database at step 540. Depending upon the age of thesehistorical mobile broadband traffic reports and the estimated confidenceassociated with that data, the method will establish a radio frequencychannel performance profile based on historical mobile broadband trafficreports at step 550. If there are no reliable historical mobilebroadband traffic reports recent enough to base an assessment upon, thecontext aware radio resource management system initiates a mobileinformation handling system radio frequency scan. This scan collectsdata regarding possible wireless links at step 560. This radio frequencyscan consumes power and processor resources so should be used sparingly,however it provides up-to-date key performance indicators (KPI) for anew radio frequency profile to be used in a mobile broadband trafficreport. Based upon this new mobile broadband traffic report, the systemprovides a wireless link performance profile to be used by the contextaware radio resource management system.

The scan or test of radio frequency links may be conducted by thecontext aware radio resource management system. As a first measure,received signal strength and bandwidth availability for a serviceprovider and a protocol are determined. Then a test of radio frequencydata capacity is made. This can test upload and download performance foreach service provider and protocol. For example, a standard test datavolume may be sent via a wireless link to a server location at theservice provider. Similarly, a test data volume may be received from aserver location by the mobile information handling system via thewireless link. Latency of response, upload and download speed orthroughput can then be measured for the service provider and protocol.The data is associated with a location zone and stamped with a time anddate. The type of transmitter/receiver or mobile information handlingsystem may also be recorded. This data set provides a wireless linkradio frequency profile that may become part of a mobile broadbandtraffic report. Upon measuring this data for a location, the report maybe shared or published by the context aware radio resource managementsystem from the mobile information handling system.

Once a radio frequency channel performance profile is submitted to thecontext aware radio resource management system and a wireless linkselected, the mobile information handling system may periodically scanmultiple wireless links or measure the selected wireless link at step570. The system may conduct testing to determine the capacity of a linkduring operation. In order to minimize radio communication and use ofresources, the network broker may be used to proactively notify a mobileinformation handling system if a wireless link selection was made usingan obsolete crowd-sourced data source. This network broker server systemmay compare time stamps of crowd-sourced data used for wireless linkselection or ranking with current time stamps of network-storedcrowd-sourced material.

Testing is similar to the testing described above. Additionally, contextaware radio resource management system may assess the quality of thewireless link being used. In addition to the capacity above, metricssuch as bit error rate (BER) and signal-to-interference metrics may beassessed. Bit error rate is the ratio of error bits to total bits sentacross a wireless link. It is a metric illustrating a signal to noiseratio which can define the quality of a radio connection for a wirelesslink. A bit error rate may be a comparison of a sent test stream of databy a transmitter with what is received by a receiver. The bit error ratecan be tested by a bit error rate tester in software which transmits aknown bit pattern to or from the mobile information handling system.Pre-error correction errors are counted. A signal-to-interference ratiomay also be measured. Such a measurement is based on the power levelsfor signal transmission (e.g., per bit) relative to interference levelsin the received signal. Packet error rate, signal-to-noise measurement,or other signal quality testing is also contemplated.

At step 580, the periodic wireless link scan updates a wireless keyperformance indicator (KPI) data matrix stored on the mobile informationhandling system. The KPI matrix establishes the spatial-temporal radiofrequency profile and comprises the data for the mobile broadbandtraffic report. The updated data is time or date stamped to establishits freshness. The system may repeat the periodic wireless link scansand update the KPI matrix for future intervals of time.

At step 590, the spatial-temporal radio frequency profile of the currentmobile broadband traffic report and any associated confidence ofestimate may optionally be advertised to the central server database foruse by other mobile information handling systems. Thus, the mobileinformation handling system may provide its contribution to the crowdsourcing data for a time and location of wireless link access.Alternatively, the mobile information handling system may store themobile broadband traffic report locally and respond to requests from acentral server database for the information.

FIG. 6 shows a method 600 for profiling link energy consumption forwireless communication links. This is an alternative embodiment to themethod of FIG. 5 for assessing spatial-temporal radio frequency profilesfor wireless links. In addition to assessment of link capacity andquality as in the method of FIG. 5, the system additionally assessesdata for device energy consumption relating to various services. In thisembodiment, the context aware radio resource management system preparesand delivers an energy link consumption report. The energy linkconsumption report provides data on power consumed by a mobileinformation handling system while performing certain tasks on a wirelesslink at a location. Energy link consumption reports contain dataindicating how many joules of energy are consumed during sending SMTPemails, sending SMS messages, conducting voice communications, accessinginternet services, streaming audio or video, or other uses of mobileinformation handling systems. This data amounts to another keyperformance indicator (KPI) in addition to capacity or link quality datafor a wireless link. The context aware radio resource management systemcan measure and utilize some or all data such as link capacity, linkquality, and energy consumption in determining preferred wireless links.Link ratings may be calculated similarly to the above description usinglink energy consumption data. If energy consumption data is unavailablehowever, the system will function with the mobile broadband trafficreports described in FIG. 5.

Scans for energy consumption information are described further below.The energy link consumption reports retrieved or compiled for the methodof FIG. 6 may also record the specific type of information handlingsystem in one embodiment. With a large number of available reports, forexample crowd sourced data, filtering for tailored energy consumptioninformation based on a make and model of a mobile information handlingsystem may better account for model-specific variations in wirelessoperation. As before, the energy link consumption reports are locationspecific and time specific. Radio frequency scans and energy consumptionmeasurements may consume resources, thus the method begins by searchingfor available link energy consumption reports.

In step 610, the context aware radio resource management system of amobile information handling system may scan for energy link consumptionreports for the device and location of operation. The scan searches forfresh, crowd sourced energy link consumption reports among dataavailable from a central server database in the wireless networks 140and 150 or located elsewhere. As described above, crowd sourcing ofenergy consumption information will enhance the availability of accurateand current data for locations and times of mobile information handlingsystem operation. A request for a fresh energy link consumption reportmay be submitted to the central server database or some other databasestoring such reports. The request may be location specific, time periodspecific, device specific or any combination of the above. Freshness maybe a parameter defined by timestamp data on a report submission. Forexample, reports submitted for a location on the same day or within thepast 24 hours may be qualified as fresh. Any limitation of time onfreshness may be used. If a time period during a day is split up on anhourly bases, a fresh report may be one that was submitted within thecurrent or previous hour of the same day. Although a different timeperiod for recent radio frequency traffic in a location may also be usedby the present embodiment.

In an alternative embodiment, data and reports may not be stored at acentral server database, or only a subset of available data may bestored there. The context aware radio resource management system maymake a request for a recent energy link consumption report fromsimilarly situated mobile information handling systems at the samelocation. This request may come indirectly via a request from thecentral server. Whether via reports stored in the central database orvia a recent request for fresh crowd sourced energy link consumptionreports, a scan for pre-existing reports may avoid the need for themobile information handling system to conduct an energy consumptionsurvey itself.

As with the broadband traffic reports for certain locations, part of thecrowd sourcing of energy link consumption report data may also involveperforming a hysteresis analysis on the data. Analyzing data frommultiple mobile information handling systems may determine trends inwireless link selection happening at a location. If many mobileinformation handling systems at a location begin to select one preferredwireless link, that link may slow down and underperform. The energy linkconsumption reports account for this crowding onto a link with thehysteresis analysis. If a large number of users begin to select a givenwireless link, then the method for generating energy link consumptionreports accounts for this factor. The method may alter which links arerecommended or in what order they are recommended.

At block 620, the method may determine that a fresh energy linkconsumption report is available for the location of the mobileinformation handling system. It does so by receiving an acknowledgmentor a fresh energy link consumption report from a central serverdatabase. At 630, the method assesses the fresh energy link consumptionreports. The method may also retrieve and include historical energy linkconsumption reports, if available. Historical energy link consumptionreports may be stored locally for the mobile information handling systemor received at the mobile information handling system from a centralserver database. These historical reports may not meet the freshnesslimitation, but may prove useful. Although historical reports may not beweighted as heavily as a fresh report, the historical reports may stilladd value or depth to the data available for a given location and time.

Assessment of energy link consumption reports are used to suggest awireless link at step 630. If conservation of battery power is apreeminent consideration, a link having the least power consumption forwireless services may be recommended. In embodiments where a weightedlist of available links is provided, selection by least-power-consumedon average may be used. The context aware radio resource managementsystem may also utilize user profile information to recommend linksbased on the most likely used wireless service or combination ofservices at a location or during a time period. The links having theleast power consumption for a heavily used service or services by themobile information handling system will be recommended.

Least-power-consumed may not always equate with recommending a wirelesslink with the greatest capacity or quality however. Although less energyconsumption often tracks the quality of a link, link quality may vastlyimprove as greater power is used in transmission. For example, higherpower consuming transmission may be used by a transmitter to improvesignal to noise ratio and, therefore, more power yields a higher qualitylink. In this case, the higher power transmission may be preferred. Incertain embodiments, detection by a mobile information handling systemof the battery state may determine the priority used. In that case, thecontext aware radio resource management system analyzes the energy linkreport in combination with a battery power level assessment indetermining recommended wireless links. In another alternative, themobile information handling system may detect connection to an AC powersource to set the priority relating to energy link consumption versusradio frequency capacity and quality. Thus, the context aware radioresource management system elects a wireless link based at least in parton the mobile information handling system power consumption assessmentand other factors as described in FIG. 2.

If no fresh energy link consumption reports are available at step 620,the method seeks stored historical energy link consumption reports fromthe central server database at step 640. Depending upon the age of thesehistorical energy link consumption reports and the estimated confidenceassociated with that data, the method will establish a mobileinformation handling system power consumption assessment on historicalenergy link consumption reports stored locally or received locally atstep 650. A link may be recommend based upon that report. Similarconsiderations to the above may be taken into account.

If there are no historical energy link consumption reports recent enoughto base an assessment upon, the context aware radio resource managementsystem initiates a mobile information handling system energy link powerscan to collect data regarding possible wireless links at step 660.Conducting this energy link power scan consumes power and processorresources, however it provides up-to-date information for a new energylink consumption report. Based upon this new energy link consumptionreport, the system provides a mobile information handling system powerconsumption assessment to be used to select a wireless link by thecontext aware radio resource management system.

A scan or test of radio frequency and energy consumption of links may beconducted by the context aware radio resource management system. Somemeasures are similar to the method of FIG. 5 to generate a radiofrequency link profile. As a first measure, signal strength andbandwidth availability for a service provider and an available protocolis determined. Then a test of radio frequency channel capacity is made.This can test upload and download performance for each service providerand protocol. For example, a standard test data volume may be sent via awireless link to a server location at the service provider. Similarly, atest data volume may be received from a server location by the mobileinformation handling system via the wireless link. Latency of response,upload and download speed or throughput can then be measured for theservice provider and protocol. In addition, the context aware radioresource management system may measure the energy consumed intransmitting or receiving the test data volume. The power consumed maytherefore be expressed in Joules or converted into a Joules/bit orJoules/byte value based on the standard test data volume. The data isassociated with a location and time and it is time and date-stamped. Thetype of transmitter/receiver or mobile information handling system mayalso be recorded. This energy consumption data may be included in awireless link radio frequency profile and become part of a mobilebroadband traffic report. Upon measuring this data for a location, thereport may be shared or published by the context aware radio resourcemanagement system from the mobile information handling system.

Once a mobile information handling system power consumption assessmentis submitted to the context aware radio resource management system and awireless link selected, the mobile information handling system mayconduct an ongoing mobile information handling system power consumptionscan for the wireless link or links being used. The context aware radioresource management system periodically measures time, location, radiofrequency profile data and energy link consumption data for the selectedwireless link or links at step 670. The data may be measured duringoperation of the mobile information handling system. Radio frequencyprofile measurements such as signal level, capacity, and signal qualitymay be measured in accordance to the description above for FIG. 5. Powerconsumption measurements for the mobile information handling systemcommunications on the wireless link are also measured.

Power consumption measurements may be conducted that are specific to themobile services used. For example, energy consumption during voicecommunications may be measured. The amount of power, for example inmilliwatts or Joules, may be expressed as a measurement per voiceminutes consumed. Power measurements of a radio frequency subsystem fromthe start of a conversation to the end of a conversation may be measuredas described above. The context aware radio resource management systemassociates this power consumption measurement with the service beingutilized. Similarly, for data transferred during internet accesses,power consumption may be measured relative to data volumes uploaded ordownloaded. The power would be measured at the active radio frequencysubsystem beginning during a download and recording the amount of dataor time of a download as well. A power-per-byte or similar measurementmay be recorded in an energy link data matrix for that location and timeof an internet access. Alternatively, power consumption measurement maybe made in terms of number of internet accesses or a combination ofaccesses and data volumes downloaded or uploaded. Since the powermeasurements themselves consume power and resources, a sampling of powerconsumption is more likely. Then estimations of power consumption may bemade during operation with a given wireless link for a service type.

In another example, audio or video streaming power consumption may bemeasured in terms of streaming minutes or data volume. Again, the radiofrequency subsystem power consumption may be sampled during the durationof a streaming session and averaged or estimated for the streamingevent. The content aware radio resource management system may alsomeasure power consumption levels for SMTP, SMS, or other messaging. Thismay be done on a per data volume of the messages or based on the numberof messages transmitted.

All of these measurements are then recorded and stored in the radiofrequency and power consumption profile as energy link matrix data. Thisinformation may be referred to as a link energy consumption report or itmay simply be part of a radio frequency profile in a mobile trafficreport.

At step 680, the data from the periodic mobile information handlingsystem power consumption scan is updated in an energy link data matrixstored on the mobile information handling system. For the given periodicscan interval, the context aware radio resource management systemupdates the energy link report matrix in the radio frequency profile.The energy link report matrix establishes the spatial-temporal mobileinformation handling system power consumption profile. The updated datais time or date stamped to establish its freshness. The system mayrepeat the periodic mobile information handling system power consumptionscans and update the energy link data matrix for future intervals oftime. Because measurement scans of this type may be costly in terms ofresources and energy consumption, the frequency of such measurements maybe limited by the context aware radio resource management system on themobile device. In one embodiment, depth of wireless link data forstatistical purposes at a given location and time may be achieved withcrowd sourcing efforts.

At step 690, the spatial-temporal power consumption profile of themobile information handling system and any associated confidence ofestimate may optionally be advertised to the central server database foruse by other mobile information handling systems. Thus, the mobileinformation handling system may provide its contribution to the crowdsourcing data for a time and location of a wireless link access.Alternatively, the mobile information handling system may store themobile broadband traffic report locally. It may optionally respond torequests from a central server database with the radio frequency andwireless link power consumption profile information or reports.

FIG. 7 shows an embodiment example method for determining an optimizedwireless link selection for a mobile device during future movement.Multiple estimations and data inputs may be analyzed by the contextaware radio resource management system. The context aware radio resourcemanagement system determines an optimal wireless link selection for themobile device in terms of cost, power consumption, or quality ofwireless channel links for connecting voice or data. FIG. 7 illustratesinput data generated via a path prediction system 705, a usage trenddetermination system to determine predicted path radio usagerequirements 710 from user profiles, and a radio link QoS assessmentsystem to determine estimated QoS scoring for radio channels 715 atfuture locations along the predicted path. Additional inputs may alsoinfluence the context aware radio resource management systemdetermination of optimized wireless link selection. Data inputs mayinclude goals or priorities 725 indicating desired priorities of cost,radio link profiles (such as QoS), or power usage from energy linkconsumption profiles. Additional data analyzed may include currentoperating states of the mobile device 730. Limitations may also beplaced on the context aware radio resource management system to preventthe benefits of the optimized wireless link selection system fromintruding too much on user experience. For example, switching too muchmay impact the efficiency benefits of the method. An example embodimentincludes inhibitors 745 that limit changes to wireless links to preventswitching.

The flow begins at 705. The context aware radio resource managementsystem utilizes a path prediction system 705 to determine a predictedfuture path of travel for the mobile device during a set of future timeintervals. The mobile path prediction system uses position data for themobile information handling system. Velocity and acceleration data aredetected by motion sensors on the mobile device or determined fromposition data. Position data may be determined via a global positioningsystem. Alternatively, a mobile positioning system via the wirelessnetwork may determine position and movement of the mobile device. Usingthis position data, the mobile path prediction system estimates apredicted future path of travel for the mobile device in a user area.

With the predicted future path, the flow proceeds at 710 to predict pathradio usage requirements for the mobile device based on context andhistory of usage. At 710, the context aware radio resource managementsystem applies usage trends for a matrix of locations to the predictedfuture path. The usage trend determination system defines a predominantservice profile of expected usage types for locations on the predictedpath according to historical trends of usage as recorded in user profiledata at those locations. The flow also proceeds to 715 where a radiolink QoS assessment system utilizes a user service matrix ofspatial-temporal radio frequency profiles for locations to determineestimated QoS scoring for radio channels 715. By applying the predictedfuture path from 705, the radio link QoS assessment system predictsradio link quality over the predicted user path for a variety of radioconnections that may be suitable for the mobile device. Wirelessintelligence reports are used to create radio link profiles forlocations. Radio link profiles may include data relating to mobilebroadband traffic and service provider link ratings. Radio link profilesof wireless radio links may also include QoS parameters of data latency,jitter of signal, packet loss statistics, and bandwidth. Minimum QoSrequirements of the mobile device will be partially determined by theexpected usage at the locations along the predicted path.

The flow proceeds to 720. At 720, the system applies optimizationpolicies for radio link selection. Optimization policies may blendconsiderations such as cost of radio link usage, power consumption ofthe mobile system to use the radio link, or quality of serviceconsiderations. The these optimization policies are applied to thedetermined predominant service profile of expected usage types and radiolink quality over the predicted future path locations. Additional inputsinto the optimized radio link selection at 720 may include factors setby the user at 725. Factors set by the user may relate to cost, powerusage, and QoS selections.

Sensors may provide additional automatic inputs into the optimized radiolink selection at 720 as well. Sensors may detect mobile device currentstate information at 730 which may include battery levels, the currentradio wireless link operating on the mobile device, and consideration ofthe most current mobile device location. Such incumbent current stateinformation will be considered to determine if making a change todifferent radio wireless connection is worthwhile. Additionally, theincumbent current state will be weighed with the risk of serviceinterruption or other factors such as whether the improvement is worththe change. For example, if the currently active radio link isdetermined to be one of the top few optimal radio links on the predictedpath, the context aware radio management system will elect not to switchradio links even if the current link is not the most optimal from acost, QoS, or power perspective. Alternatively, if the weighted QoSparameters of the currently operating link are meet the minimumrequirements or are within a threshold level of deviation from the mostoptimal radio link, then no switch of radio link will occur.

After application of the optimization policies at 720, the flow proceedsto decision diamond 733 for the application of a location validationfilter 733. The location validation filter determines whether thepredicted future path for the mobile information system is stillaccurate based on the most recent location measurement. If a suddenchange in location and trajectory are detected that deviate from thepredicted future path at this stage in the method, the locationvalidation filter rejects the predicted path. Upon rejection, the flowreturns to 705 to repeat the process of predicting a future path for themobile device. If the location validation filter detects a recentlocation measurement still in or near the predicted future path, thisvalidates the predicted future path and the flow proceeds to 735.

At 735 the method applies the changes to radio wireless link or radioband on the mobile device. Inputs are received at 735 that may overridethe radio link change command. For example, override commands set by auser or data service provider (not shown) may restrict application of achange to the wireless link used by the mobile device. Inihibitors 745may also alter implementation of the command to switch wireless links.Inhibitors 745 are based on several factors including time ofprogression through the predicted future path, locations, and QoSconsiderations. These inhibitors 745 are used to inhibit highly frequentwireless link changes that could actually cost the mobile device systemrather than improve performance. Additional inhibitors 745 includerestrictions based on location, such as if the mobile device is in anairplane or at a work location where limitations may be placed onwireless link options. For example, an airplane may be restricted to aWI-FI access. An office location may have restrictions fororganization-issued mobile devices limiting wireless link access to WLANaccess for cost or security reasons while the mobile device is on theorganization's premises. If an override command or the inhibitors 745 donot override the changes, then the context aware radio resourcemanagement system executes commands to make the wireless radio linkchange.

In an alternative embodiment, the method of FIG. 7 may issueoptimization policies at 720 and transmit a recommendation to a userrather than execute instructions to automatically change the wirelesslink. In this way, the user may be presented with an option to elect tochange to an optimized wireless link. The user may change wireless linksmanually, or may elect to have the change made automatically byselecting an option to switch whereby the flow would proceed to executethe change of wireless link as described above. In another alternativeembodiment, the user may be presented with a limited number of optimizedwireless link options at 720 and may select from among the optimalwireless links for automatic execution of switching during a predictedfuture path.

FIG. 8 shows method for predicting future mobile device path locationssuch as with a mobile path prediction system as part of the contextaware radio resource management system. The method begins at 805 wherethe mobile path prediction system determines the position of a mobiledevice. The mobile path prediction system may operate via execution ofinstructions via a processor on the mobile information handling systemor via a processor on one or more information handling systems incommunication with the mobile information handling system via a networkconnection. For example, the latter may be a cloud based context awareradio resource management system. The mobile information handling systemposition is detected. To determine velocity, acceleration and direction,an extrapolation of multiple measured position data points may be used.For example, multiple position data points may be taken to determinedirection, velocity and acceleration such as via a global positioningsystem. Alternatively, a mobile positioning system using radio signalsstrength and location measurements with respect to one or more celltower locations via a wireless network may determine mobile deviceposition as is known in the art. In an alternative embodiment, themobile device may have motion sensors integrated to determine direction,velocity, and acceleration. With the motion sensors, at least oneposition data point is needed. Example motion sensors includegeomagnetic reference sensors and any combination of accelerometers andgyroscopic sensors. The position data and any detected velocity andacceleration data is reported to the context aware radio resourcemanagement system.

The flow proceeds to 810 where the mobile path prediction systemprojects multiple probable trajectories for the mobile device(s) atfuture time intervals. This is done via extrapolating position,direction, velocity and acceleration to a plurality of future timeintervals. The locations at the plurality of time intervals establishtrajectory paths. Multiple trajectories are determined so that for eachfuture time interval there is a plurality of possible future locations.Proceeding to 815, the mobile path prediction system of the contextaware radio resource management system applies probability statistics tothe multitude of future path locations. In the present embodiment, alinear mean square estimation is applied to the determined trajectorylocations and less probable path locations are discarded. In an exampleembodiment, the path prediction system applies a Kalman filterprobability estimation to the probable trajectory locations to filterout lowest probability path locations.

The flow proceeds to 820, where the mobile path prediction systemdetermines a predicted preliminary path for several locationscorresponding to upcoming intervals of time. This preliminary predictedpath is then mapped to a bin map depicting a user area at 825. In anexample embodiment, the bin map includes a grid of latitude andlongitude coordinates for future mobile device path locations. Such anexample is illustrated further below with respect to FIG. 9A.

Proceeding to 830, the context aware radio resource management systemaccesses a location matrix having historic visitation data for themobile information handling system. The history of visitation isrecorded from user profile data for mobile devices as described above.The visitation history location matrix may be also mapped to a bin mapof user area. The visitation history location matrix contains data aboutthe frequency and time spent at locations and may also include temporalinformation relating to times during the day when such visitation ismade. In this way, the visitation history location matrix will containinformation relating to cyclostationary daily habits of a mobile deviceuser's visitation.

The context aware radio resource management system proceeds to 835. At835, the path prediction system portion correlates the preliminarypredicted path with the visitation history location matrix. Thepreliminary predicted path begins as a selected mobile devicetrajectory. In the example embodiment, this may be done via overlay ofbin maps containing both preliminary predicted path and the visitationhistory information for locations near the preliminary predicted path.An example visitation history matrix bin map is shown in FIG. 9B below.Nearby locations for the visitation history matrix may be limited tothose locations that fall within a certain number of bin map grid boxesfrom the preliminary predicted path. How many bin map grid boxes areused as nearby locations will depend on the physical size of each binmap grid box and factors such as how many future time intervals are usedto determine the predicted future path.

The flow proceeds to 840 where the path prediction system modifies thepreliminary predicted path locations based on the visitation historylocation matrix data. The path prediction system modifies thepreliminary predicted path to include a location on the visitationhistory location matrix depending on the frequency of visitation to thatlocation. Additional factors in modifying the preliminary predicted pathmay include the nearness of the frequently visited grid map box locationto the preliminary predicted path. For example, a highly visitedlocation one grid box away from the preliminary predicted path willcause a modification of the preliminary predicted path. However, a lessvisited location three or more grid boxes away from a preliminarypredicted path location will unlikely cause a modification to thepreliminary predicted path. The mobile path prediction system sets athreshold of factors to determine at what point the modification to thepreliminary path will occur. Application of a set of conditionalprobabilities, such as with Bayesian classifier statistics, may takeinto account several variables such as proximity to trajectory andfrequency of visitation to determine where to predict future pathlocations. Another factor having impact on modifying the preliminarypredicted path includes the time of day. Time of day takes into accountcyclostationary considerations such as daily routines of the mobiledevice user. The modification of the preliminary predicted path mayoccur in a recursive fashion to correlate additional probabilityestimation of a location along the preliminary predicted path until apredicted future path is determined.

In one embodiment of the application of determining the predicted pathis based on probability that a mobile information handling system visitsa location during a daily time interval. By way of example, probabilityof visiting a location may be determined as follows:Probability of visiting a location(x _(i) ,y _(i),t+interval)=Historical Probability of visiting (x _(i) ,y _(i),t+interval)*Normalized Distance Computation,whereNormalized Distance Computation=1/SQRT(2π)*exponential(distance of alocation from a preliminary path location);and whereDistance=[Places Historically visited(xi, yi, t)−Predicted Locationutilizing a Kalman Filter(t+interval)]²/σ².

x_(i), y_(i)=potential locations visited during prediction interval

σ=variance in location prediction,

Interval=mobile prediction path time period.

The mobile path prediction system selects a path x_(i), y_(i) with thehighest Bayesian posterior probability given the preliminary predictedpath. Of course, other probability computations are also contemplatedusing distance from the preliminary predicted path and history ofvisiting a location in the user area.

At 845, the mobile prediction path system establishes the selectedpredicted path over the future time intervals including modificationsfrom 840. Proceeding to 850, the mobile prediction path system appliesthe modified predicted future path to the bin map of the user area forthe mobile device. This predicted future path and bin mapping is used bythe context aware radio resource management system at later phases ofradio link selection.

FIG. 9A depicts a bin map 900 with example latitude 905 and longitude910 coordinates upon which several types of information may be set overthe bin map by the context aware radio resource management system. Thegrid boxes 915 on the bin maps 900 of FIGS. 9A, 9B, and 9C, maydetermine the granularity with which a location is defined. In theexample embodiment of FIGS. 9B and 9C the grid squares representapproximately one half kilometer by one half kilometer. The overlay gridsquare information may include a predicted future path 920 as shown inFIG. 9A. FIG. 9B depicts historic visitation matrix information 930 inan overlay of grid squares 915 on the bin map 900. Such grid squaresidentify locations visited by the mobile device. A third dimension,pattern or color indication (not shown) may be used to show frequency ofvisitation or ranges of visitation frequency applied to locations 915 onthe bin map 900. Additional data may reflect the mobile devicerequirements at locations 915. The mobile device requirements reflectexpected wireless service type usage at visited locations. Again, colorsor patterns or a third dimension on grid boxes 915 may be used on thebin map 900 to show predominant usage expected at grid box locations onthe bin map 900. FIG. 9C may show a bin map 900 having estimated QoSlevels for the variety of wireless links available at grid box locations915. As with the other bin maps, colors or patterns or a third dimension955 on the grid boxes 915 may be used on the bin map 900 to show QoSranges or energy consumption data for wireless link sources at depictedgrid box locations. The measured QoS data and energy link consumptiondata is from a plurality of wireless intelligence reports for locationsin the user area.

FIG. 10 shows a method for defining the expected minimum QoSrequirements for the mobile device along a predicted future path. At1005, the position of the user is determined including latitude,longitude and time to identify time and location of the mobile device.Proceeding to 1010, the system determines the predicted future path ofthe information handling system in accordance with the disclosuresabove. An example predicted path on a bin map with grid coordinatesystem is shown at 1015 similar to FIG. 9A above. At 1020, new datarelating to wireless service types are collected by the system inaccordance with disclosures above. This usage trend data updates thehistorical wireless service type profiles as part of the user profilesfor locations in the user area at 1025. The user area may be of anyscope. It is contemplated that a user area may be worldwide, within acountry or state, or within a metropolitan area. In alternativeembodiments the user area may be limited to an expected area of usagebased on previous visitation history or realistic limits on likelytravel in the contemplated future time interval. In a furtherembodiment, user area may be limited to areas within reasonable distancefrom the predicted future path of the mobile information handlingsystem. Limiting the user area is helpful to reduce the data set usedfor analysis.

The flow proceeds to 1030 where the method compares the predicted futurepath with the historical wireless service type profiles for thelocations in or near the predicted future path. This comparison ofwireless service types used at locations along the predicted path isaveraged and a predominant wireless service type profile is determinedover the predicted future path. An example wireless service type profileis depicted at 1035 showing predicted percentages of use of wirelessservice types based on historical use at the locations in the predictedpath. The predominant wireless service type profile for the path may bebounded with data from similar times of day to the predicted future pathtravel time. Alternatively, historical wireless service profile data maybe taken for any daily time intervals such as when wireless servicedepends more strictly on location rather than time of day.

With a predominant wireless service type profile 1035 of expected usagetypes for the predicted future path, the method accesses policy settingsfor QoS requirements for service types. An example policy table for QoSrequirements by service type is shown at 1040. The QoS requirementstable shows the minimum requirements for various QoS parametersaccording to wireless service type. QoS parameters for this embodimentinclude latency, packet loss, jitter and bandwidth (BW). Tolerancelevels are shown in this policy table for voice, SMS, streaming data,email, http downloads, ftp downloads, and other wireless data servicetypes. In the shown example at 1040, voice service and streamingapplications can tolerate very little latency (<150 msec and <500 msecrespectively) or jitter (<50 msec²) whereas SMS and email applicationscan tolerate substantially more latency (<5000 msec) and jitter (<200msec² and <500 msec²). For bandwidth (BW) however, voice requirescomparatively low bandwidth (>30 kbps) similar to SMS and email, whereasstreaming requires comparatively high bandwidth (>1000 kbps). With thepredominant wireless service type profile 1035 for the predicted pathdetermined, the method applies the QoS requirements policy at 1045.Proceeding to 1050, the minimum QoS requirements are weighted accordingto expected wireless service usage percentages over the predicted path.This may be achieved by multiplying the percentages of the wirelessservice type profile 1035 as weighting factors to the QoS requirementspolicy shown as 1040. In another embodiment, the method selects one ormore predominant wireless service types that are expected to be used andselects for QoS criteria from the policy table 1040 based on thepredominant wireless service type or types. By way of example in FIG.10, the predominant wireless service types would be voice and SMS. At1035 and 1040 the expected predominant usage would require relativelylow latency (due to prominence of voice and to a lesser degree due tostreaming), low packet loss (due to prominence of voice and SMS), andlow jitter (due to voice). However, the QoS requirements would also onlyrequire a relatively low bandwidth (due to prominence of voice and SMS,and to a lesser degree email usage). This is applied unless a streamingapplication were detected to be actively in use as discussed more below.The usage trend determination system of the context aware radio resourcemanagement system performs the above described method.

FIG. 11 shows another method embodiment for defining the expectedminimum QoS requirements for the mobile device along a predicted futurepath. The method begins at 1105 where the context aware radio resourcemanagement system predicts a future path, for example similar to thatshown in FIG. 9A. The predicted future path for the mobile informationhandling system is determined according to the disclosures herein, forexample in FIG. 8. The flow proceeds to 1110 where the usage trenddetermination system accesses a wireless service type profile matrixfrom mobile device user profiles for locations in a user's area. Theusage trend determination system selects a wireless service type profilefor a location in the predicted future path. Proceeding to 1115, themethod accesses QoS requirements policy as set for a plurality wirelessservice types similar to the policy table 1040 shown above in FIG. 10.At 1120, the method applies the QoS requirements sufficient to providewireless service to the plurality of wireless service types profiled forthe location.

At 1125, method applies weighting to the QoS requirements from thepolicy settings according to expected wireless service type usage forthe location. The flow proceeds to decision diamond 1130. At 1130, themethod determines if there are additional locations in the predictedfuture path for the mobile information handling system. If so, the flowreturns to 1110 to repeat the process for the next location in thepredicted future path. QoS requirements for locations along thepredicted future path may be applied to a bin map for grid squarelocations along the predicted future path.

If there are no additional locations in the predicted future path forthe mobile device, the flow proceeds to 1135. The method averages theweighted QoS requirements for the expected usage levels over alllocations in the predicted future path of the mobile device. Withaverage weighting for all locations along the predicted future path, theusage trend determination system of the context aware radio resourcemanagement system can define a predominant set of QoS requirements overthe predicted future path at 1140. This predominant set of QoSrequirements is weighted by the wireless service type profiles for thepredicted future path.

The flow proceeds to decision diamond 1145 where the system determinesif one wireless service type is currently in use as the mobile device isabout to enter the predicted future path. If not, the method ends. Ifso, the flow proceeds to 1150 where context aware radio resourcemanagement system adjusts the QoS requirements for the predicted futurepath according to the actively used wireless service. This acts as anoverride to determining QoS requirements for the mobile device that maycontradict QoS requirements for the mobile device that is actively usinga wireless service. At this point, the flow ends and the mobile deviceQoS requirements are determined for the predicted future path.

FIG. 12 shows a method of predicting radio link quality of service,power consumption, and costs over the predicted user path for aplurality of radio connections. The method also shows utilizing thepredicted radio link quality, cost and power consumption to select anoptimized radio link and create a policy for linking or switching radiolinks for the mobile device. A wireless link QoS assessment system ofthe context aware radio resource management system utilizes a radio linkmatrix of spatial-temporal radio frequency profiles with QoS datacollected for a plurality of locations in a user area. This radio linkmatrix data is used to determine estimated QoS scoring for radiochannels at locations in the user area. An example of such a radio linkmatrix of radio link quality measurements is shown in FIG. 9C asdepicted on a bin map of a user area.

At 1205, the position of the user is determined including latitude,longitude and time to identify time and location of the mobile device.Proceeding to 1210, the system determines the predicted future path ofthe information handling system in accordance with the disclosuresabove. At 1215, new data relating to radio link measurements accordingto location according to positional latitude and longitude may becollected from a plurality of mobile devices. The context aware radiomanagement system may include crowd-sourced data for radio links orchannels of radio connections. The new radio link measurements may alsoinclude a time component so radio service levels and quality of servicemay be measured according to time of day. Such collection of radio linkmeasurements may be conducted in accordance with methods and systemsdescribed above.

At 1220, the radio link measurements are included in the matrix of radiolink measurements according to location, time, and even type of radioservice. Types of radio links can include a type of wireless link, suchas Wi-Fi/WLAN link or macro-cellular wireless links such as 2G, 3G, 4Gand similar future wireless links. Types of radio links may also includemacro-cellular wireless links from a variety of service providers.Proceeding to 1225, the predicted radio link quality for a plurality ofwireless links and service providers is determined over the predictedfuture path of the mobile device. This anticipated radio link QoSincludes QoS parameters for locations along the predicted future mobileinformation handling system path. Additionally, average QoS parametersfor all locations along the predicted future path may be determined forthe wireless link types.

The flow proceeds to 1235 where the method compares predicted radio linkquality for the predicted future path of 1225 with the minimum mobiledevice QoS requirements 1230, such as determined according to the methodembodiments of FIGS. 10 and 11. At 1235, the wireless link QoSassessment system matches the parameters for the minimum mobile deviceQoS requirements 1230 in the predicted future path with the predictedQoS parameter levels for a plurality of radio links. In this way, anoptimized radio link selection may be made at 1235 by the context awareradio resource management system. In the embodiment of FIG. 12, QoS ofthe radio link has been described as the overriding consideration forselection of an optimized wireless link at 1235.

Other factors may also be considered however in additional embodiments.State of the device and user-desired settings may also be assessed inselecting the optimized radio link at 1235. For example, the state ofthe battery level or access to a power source may be detected. Limitedpower supply levels may influence selection of a wireless link based onenergy link consumption measurements as stored with the radio linkmatrix of spatial-temporal radio frequency profiles and used topredicted power consumption levels for the predicted future path of themobile device. Additionally, cost of wireless link access may beconsidered when selecting a wireless link. For example, cost of accessto macro-cellular wireless links may vary widely among wireless serviceproviders. In another example, a Wi-Fi wireless link may be a freeoption that would be preferred by the user over a macro-cellularwireless link.

The flow proceeds to 1240, where the context aware radio resourcemanagement system creates a radio link selection policy based on theuser location and usage context. This radio link selection policy may betransmitted as a recommendation to the user in one embodiment. Inanother embodiment, it may create a wireless link switching commandsubject to inhibitors or override settings as described above in FIG. 7.

In an alternative embodiment, locations or wireless links that cannotmeet the minimum QoS requirements of the expected wireless service typeusages by the may be designated by the context aware radio resourcemanagement system as dead zones, at least for a particular type ofwireless link is unavailable or of such low QoS that it cannot beeffectively used. These dead zones may also become part of the radiolink selection policy as wireless links to be avoided.

FIG. 13 shows another embodiment of a method for predicting radio linkquality of service, power consumption, and costs over the predicted userpath for a plurality of radio connections. The method also showsutilizing the predicted radio link quality, cost and power consumptionto select an optimized radio link and create a policy for switchingradio links by the mobile device.

The method begins at 1305 where he wireless link QoS assessment systemof the context aware radio resource management system accesses apredicted future path for the mobile information handling system, forexample similar to that shown in FIG. 9A. The flow proceeds to 1310where the wireless link QoS assessment system accesses a radio linkmatrix for locations in a user's area. Proceeding to 1315, the methodselects radio link profiles for multiple wireless links at a location inthe predicted future path.

The flow proceeds to decision diamond 1320 where it is determinedwhether there is another location in the predicted future path for whicha radio link profile has yet to be selected. If so, the flow proceedsback to 1310 to access the radio link matrix and select a radio linkprofile for the next location at 1315. If not, the flow proceeds to 1325where the context aware radio resource management system predicts radiolink quality for multiple wireless links over the predicted future pathbased on previously reported link quality from the radio link matrix. Asdescribed before, the radio link matrix may contain crowd sourced datameasured from wireless intelligence reports and reported from aplurality of mobile devices that have visited the location. It includesQoS parameters such as latency, jitter, packet loss, and bandwidth. Itmay also contain information relating to power consumption forcommunication via the plurality of wireless links from energy linkconsumption profiles. And the radio link quality information may includea time component relating to time of day for radio transmission on theplurality of wireless links at a location. FIG. 9C shows an example ofthe predicted radio link quality in an overlay on a bin map of a userarea.

The flow proceeds to 1330 where the context aware radio resourcemanagement system accesses the weighted QoS requirements for the mobiledevice over the predicted future path. These requirements are derived,for example, via the method embodiments described above with respect toFIGS. 10 and 11. FIG. 9C also illustrates an example bin map with anoverlay depicting QoS requirements for the mobile device over the futurepredicted path. At 1335, the method matches the QoS requirements for themobile device with the predicted radio link QoS parameters for thepredicted future path of the mobile device. Matching the weighted QoSrequirements for the mobile device, the system determines which radiolinks have predicted QoS parameters that most align with the weightedQoS requirements of the mobile device. Additional factors may beconsidered when selecting one or more optimized wireless links at 1335.The context aware radio resource management system may also determinebattery power levels and match wireless links that will draw minimalpower. In addition, the context aware radio resource management systemmay select among the cost of utilizing various wireless links whenselecting which wireless link is optimal at 1335.

The context aware radio resource management system may then proceed to1340, where the method transmits a recommended optimal wireless link orsubset of links to a user to select whether to switch radio linkconnections. In one embodiment the process then ends. In an alternativeembodiment, the method proceeds to decision diamond 1345 where thesystem determines if an override command or setting exists to prevent anautomatic switch of radio link. If so, the flow ends with the override.If not, the flow proceeds to decision diamond 1350, where the contextaware radio resource management system determines if an inhibitor wouldprevent switching of a wireless link. For example, a wireless linkswitch has recently occurred. For example, a time threshold since themost recent switching may be used to trigger an inhibitor. If aninhibitor prevents a switch of wireless links by the context aware radioresource management system, the flow then ends. If not, the contextaware radio resource management system issues a command to switch to anoptimal wireless link as determined for the predicted future path basedon one or more factors of matching radio link QoS parameters to mobiledevice QoS requirements, power consumption, and cost.

FIG. 14 shows an information handling system 1400 capable ofadministering each of the specific embodiments of the presentdisclosure. The information handling system 1400 can represent the userinformation handling systems 110, 120, and 130 or servers or systemslocated anywhere within network 100 of FIG. 1, including the remote datacenter 186 operating the virtual machine applications described herein.The information handling system 1400 may include a processor 1402 suchas a central processing unit (CPU), a graphics processing unit (GPU), orboth. Moreover, the information handling system 1400 can include a mainmemory 1404 and a static memory 1407 that can communicate with eachother via a bus 1408. As shown, the information handling system 1400 mayfurther include a video display unit 1410, such as a liquid crystaldisplay (LCD), an organic light emitting diode (OLED), a flat paneldisplay, a solid state display, or a cathode ray tube (CRT).Additionally, the information handling system 1400 may include an inputdevice 1412, such as a keyboard, and a cursor control device, such as amouse. The information handling system may include a power source suchas battery 1414 or an A/C power source. The information handling system1400 can also include a disk drive unit 1416, and a signal generationdevice 1418, such as a speaker or remote control. The informationhandling system 1400 can include a network interface device such as awireless adapter 1420. The information handling system 1400 canrepresent a server device whose resources can be shared by multipleclient devices, or it can represent an individual client device, such asa desktop personal computer, a laptop computer, a tablet computer, or amobile phone.

The information handling system 1400 can include a set of instructions1424 that can be executed to cause the computer system to perform anyone or more of the methods or computer based functions disclosed herein.For example, instructions 1424 may execute the context aware radioresource management system disclosed herein. In a further example,processor 1402 may conduct processing of wireless service usage by theinformation handling system 1400 according to the systems and methodsdisclosed herein. The computer system 1400 may operate as a standalonedevice or may be connected such as using a network, to other computersystems or peripheral devices.

In a networked deployment, the information handling system 1400 mayoperate in the capacity of a server or as a client user computer in aserver-client user network environment, or as a peer computer system ina peer-to-peer (or distributed) network environment. The informationhandling system 1400 can also be implemented as or incorporated intovarious devices, such as a personal computer (PC), a tablet PC, aset-top box (STB), a PDA, a mobile information handling system, apalmtop computer, a laptop computer, a desktop computer, acommunications device, a wireless telephone, a land-line telephone, acontrol system, a camera, a scanner, a facsimile machine, a printer, apager, a personal trusted device, a web appliance, a network router,switch or bridge, or any other machine capable of executing a set ofinstructions (sequential or otherwise) that specify actions to be takenby that machine. In a particular embodiment, the computer system 1400can be implemented using electronic devices that provide voice, video ordata communication. Further, while a single information handling system1400 is illustrated, the term “system” shall also be taken to includeany collection of systems or sub-systems that individually or jointlyexecute a set, or multiple sets, of instructions to perform one or morecomputer functions.

The disk drive unit 1416 may include a computer-readable medium 1422 inwhich one or more sets of instructions 1424 such as software can beembedded. The disk drive unit 1416 also contains space for data storage.Further, the instructions 1424 may embody one or more of the methods orlogic as described herein. For example, instructions relating to thecontext aware radio resource management software algorithms may bestored here. Additionally, parameters and profiles relating to contextaware radio resource management system may be stored here. Parametersmay include communication and efficiency rules or data relating todevice-specific capabilities. Profiles stored here may include end-userprofile data measured by the processor 1402 during wireless serviceusage processing. Profiles may additionally include crowd sourcespatial-temporal radio frequency profiles for wireless links or energylink consumption data. In a particular embodiment, the instructions,parameters, and profiles 1424 may reside completely, or at leastpartially, within the main memory 1404, the static memory 1407, and/orwithin the processor 1402 during execution by the information handlingsystem 1400. The main memory 1404 and the processor 1402 also mayinclude computer-readable media. Battery 1414 may include a smartbattery system that tracks and provides power state data 1426. Thispower state data may be stored with the instructions, parameters, andprofiles 1424 to be used with the systems and methods disclosed herein.

The network interface device shown as wireless adapter 1420 can provideconnectivity to a network 1428, e.g., a wide area network (WAN), a localarea network (LAN), wireless local area network (WLAN), a wirelesspersonal area network (WPAN), a wireless wide area network (WWAN), orother network. Connectivity may be via wired or wireless connection.Wireless adapter 1420 may include one or more radio frequency subsystems1430 with transmitter/receiver circuitry, wireless controller circuitry,amplifiers and other circuitry for wireless communications. Eachradiofrequency subsystem 1430 may communicate with one or more wirelesstechnology protocols. The radiofrequency subsystem 1430 may containindividual subscriber identity module (SIM) profiles for each technologyservice provider and their available protocols. Alternatively it mayhave a software based SIM profile that is reconfigurable. The wirelessadapter 1420 may also include antenna system 1432 which may be tunableantenna systems for use with the system and methods disclosed herein.

In an alternative embodiment, dedicated hardware implementations such asapplication specific integrated circuits, programmable logic arrays andother hardware devices can be constructed to implement one or more ofthe methods described herein. Applications that may include theapparatus and systems of various embodiments can broadly include avariety of electronic and computer systems. One or more embodimentsdescribed herein may implement functions using two or more specificinterconnected hardware modules or devices with related control and datasignals that can be communicated between and through the modules, or asportions of an application-specific integrated circuit. Accordingly, thepresent system encompasses software, firmware, and hardwareimplementations.

In accordance with various embodiments of the present disclosure, themethods described herein may be implemented by software programsexecutable by a computer system. Further, in an exemplary, non-limitedembodiment, implementations can include distributed processing,component/object distributed processing, and parallel processing.Alternatively, virtual computer system processing can be constructed toimplement one or more of the methods or functionality as describedherein.

The present disclosure contemplates a computer-readable medium thatincludes instructions, parameters, and profiles 1424 or receives andexecutes instructions, parameters, and profiles 1424 responsive to apropagated signal; so that a device connected to a network 1428 cancommunicate voice, video or data over the network 1428. Further, theinstructions 1424 may be transmitted or received over the network 1428via the network interface device or wireless adapter 1420.

Information handling system 1400 includes one or more applicationprograms 1424, and Basic Input/Output System and firmware (BIOS/FW) code1424. BIOS/FW code 1424 functions to initialize information handlingsystem 1400 on power up, to launch an operating system, and to manageinput and output interactions between the operating system and the otherelements of information handling system 1400. In a particularembodiment, BIOS/FW code 1424 reside in memory 1404, and includemachine-executable code that is executed by processor 1402 to performvarious functions of information handling system 1400. In anotherembodiment (not illustrated), application programs and BIOS/FW codereside in another storage medium of information handling system 1400.For example, application programs and BIOS/FW code can reside in drive1416, in a ROM (not illustrated) associated with information handlingsystem 1400, in an option-ROM (not illustrated) associated with variousdevices of information handling system 1400, in storage system 1407, ina storage system (not illustrated) associated with network channel 1420,in another storage medium of information handling system 1400, or acombination thereof. Application programs 1424 and BIOS/FW code 1424 caneach be implemented as single programs, or as separate programs carryingout the various features as described herein.

While the computer-readable medium is shown to be a single medium, theterm “computer-readable medium” includes a single medium or multiplemedia, such as a centralized or distributed database, and/or associatedcaches and servers that store one or more sets of instructions. The term“computer-readable medium” shall also include any medium that is capableof storing, encoding, or carrying a set of instructions for execution bya processor or that cause a computer system to perform any one or moreof the methods or operations disclosed herein.

In a particular non-limiting, exemplary embodiment, thecomputer-readable medium can include a solid-state memory such as amemory card or other package that houses one or more non-volatileread-only memories. Further, the computer-readable medium can be arandom access memory or other volatile re-writable memory. Additionally,the computer-readable medium can include a magneto-optical or opticalmedium, such as a disk or tapes or other storage device to storeinformation received via carrier wave signals such as a signalcommunicated over a transmission medium. Furthermore, a computerreadable medium can store information received from distributed networkresources such as from a cloud-based environment. A digital fileattachment to an e-mail or other self-contained information archive orset of archives may be considered a distribution medium that isequivalent to a tangible storage medium. Accordingly, the disclosure isconsidered to include any one or more of a computer-readable medium or adistribution medium and other equivalents and successor media, in whichdata or instructions may be stored.

In the embodiments described herein, an information handling systemincludes any instrumentality or aggregate of instrumentalities operableto compute, classify, process, transmit, receive, retrieve, originate,switch, store, display, manifest, detect, record, reproduce, handle, oruse any form of information, intelligence, or data for business,scientific, control, entertainment, or other purposes. For example, aninformation handling system can be a personal computer, a consumerelectronic device, a network server or storage device, a switch router,wireless router, or other network communication device, a networkconnected device (cellular telephone, tablet device, etc.), or any othersuitable device, and can vary in size, shape, performance, price, andfunctionality. The information handling system can include memory(volatile (e.g. random-access memory, etc.), nonvolatile (read-onlymemory, flash memory etc.) or any combination thereof), one or moreprocessing resources, such as a central processing unit (CPU), agraphics processing unit (GPU), hardware or software control logic, orany combination thereof. Additional components of the informationhandling system can include one or more storage devices, one or morecommunications ports for communicating with external devices, as wellas, various input and output (I/O) devices, such as a keyboard, a mouse,a video/graphic display, or any combination thereof. The informationhandling system can also include one or more buses operable to transmitcommunications between the various hardware components. Portions of aninformation handling system may themselves be considered informationhandling systems.

When referred to as a “device,” a “module,” or the like, the embodimentsdescribed herein can be configured as hardware. For example, a portionof an information handling system device may be hardware such as, forexample, an integrated circuit (such as an Application SpecificIntegrated Circuit (ASIC), a Field Programmable Gate Array (FPGA), astructured ASIC, or a device embedded on a larger chip), a card (such asa Peripheral Component Interface (PCI) card, a PCI-express card, aPersonal Computer Memory Card International Association (PCMCIA) card,or other such expansion card), or a system (such as a motherboard, asystem-on-a-chip (SoC), or a stand-alone device). The device or modulecan include software, including firmware embedded at a device, such as aPentium class or PowerPC™ brand processor, or other such device, orsoftware capable of operating a relevant environment of the informationhandling system. The device or module can also include a combination ofthe foregoing examples of hardware or software. Note that an informationhandling system can include an integrated circuit or a board-levelproduct having portions thereof that can also be any combination ofhardware and software.

Devices, modules, resources, or programs that are in communication withone another need not be in continuous communication with each other,unless expressly specified otherwise. In addition, devices, modules,resources, or programs that are in communication with one another cancommunicate directly or indirectly through one or more intermediaries.

Although only a few exemplary embodiments have been described in detailherein, those skilled in the art will readily appreciate that manymodifications are possible in the exemplary embodiments withoutmaterially departing from the novel teachings and advantages of theembodiments of the present disclosure. Accordingly, all suchmodifications are intended to be included within the scope of theembodiments of the present disclosure as defined in the followingclaims. In the claims, means-plus-function clauses are intended to coverthe structures described herein as performing the recited function andnot only structural equivalents, but also equivalent structures.

What is claimed is:
 1. An information handling system comprising: awireless adapter to communicate with a wireless link; a storage deviceto store a spatial-temporal user profile comprising wireless deviceusage trend data for a plurality of locations where the informationhandling system has operated; a positional detector to detect positionof the information handling system; an application processor todetermine a trajectory estimation during a future time interval for theinformation handling system from position data; the applicationprocessor to correlate the wireless device usage trend data for alocation in or near the trajectory estimation; and the applicationprocessor to select a predicted future information handling system pathduring the future time interval based on correlation between thetrajectory estimation and the wireless device usage trend data, whereinthe application processor selects the predicted future informationhandling system path based on a correlation between a plurality ofpreviously visited locations and nearness to a location in thetrajectory estimation during the future time interval.
 2. The system ofclaim 1, wherein the positional detector detects position via asatellite global positioning system and further detects position dataincluding direction, velocity and acceleration of the informationhandling system.
 3. The system of claim 1, wherein the applicationprocessor determines the trajectory estimation for the informationhandling system during the future time interval based on application ofa linear mean square estimator to estimate future locations usingcurrent position, velocity and acceleration.
 4. The system of claim 1,wherein the application processor further selects a location in thepredicted future information handling system path by assessing avisitation frequency to a location recorded in the wireless device usagetrend data and by assessing the proximity of the location to thetrajectory estimation for the information handling system during thefuture time interval.
 5. The system of claim 1, wherein the applicationprocessor further selects the predicted future information handlingsystem path by modifying the trajectory estimation for the informationhandling system during the future time interval to include frequentlyvisited locations within one grid square from the trajectory estimationon a location map grid.
 6. The system of claim 1, wherein theapplication processor selecting the predicted future informationhandling system path is conducted via a remotely-hosted application andcommunicated to the information handling system.
 7. The system of claim4, wherein the application processor selects a location in the predictedfuture information handling system path from among several possiblefuture information handling system locations further based on apreviously visited location having a highest visitation frequency level.8. A computer implemented method comprising: storing a spatial-temporaluser profile comprising wireless device usage trend data for a pluralityof locations where a mobile information handling system has operated;detecting, via a positional detector, a position of the mobileinformation handling system; predicting, via an application processor, afuture path of the mobile information handling system based on atrajectory estimation during a future time interval for the informationhandling system determined from detected position data; and correlatingthe trajectory estimation during the future time interval with thewireless device usage trend data for a location in or near thetrajectory estimation, wherein correlating the trajectory estimationduring the future time interval with historical usage trend dataincludes assessing a visitation frequency to a location recorded in theusage trend data.
 9. The method of claim 8, wherein determining thetrajectory estimation during the future time interval is based onapplication of a linear mean square estimator to estimate of theprobability of future locations using detected position data includingcurrent position, velocity and acceleration of the mobile informationhandling system.
 10. The method of claim 8, wherein correlating thetrajectory estimation during the future time interval with historicalusage trend data is conducted on the mobile information handling system.11. The method of claim 8, wherein predicting the future path of themobile information handling system includes modifying the trajectoryestimation to include frequently visited locations within one gridsquare on a location map.
 12. The method of claim 8, wherein predictingthe future path of the mobile information handling system includesselecting from several probable future mobile information handlingsystem locations along the trajectory estimation based on a distancebetween locations in the trajectory estimation and a previously visitedlocation.
 13. The method of claim 12, wherein predicting the future pathof the mobile information handling system further includes selectingfrom several possible future mobile information handling systemlocations along the trajectory estimation based on the previouslyvisited location having a highest visitation frequency level.
 14. Aninformation handling system comprising: a network interface device toreceive detected position data; a storage device to store aspatial-temporal user profile comprising wireless device usage trenddata for a plurality of locations where a mobile information handlingsystem has operated; an application processor to determine a trajectoryestimation during a future time interval for the mobile informationhandling system based on received position data; the applicationprocessor to correlate the trajectory estimation with the wirelessdevice usage trend data for a location in or near the trajectoryestimation; and the application processor to select a predicted futuremobile information handling system location during the future timeinterval from several possible future mobile information handling systemlocations along the trajectory estimation based a proximity of thelocation to the trajectory estimation.
 15. The information handlingsystem of claim 14, wherein the position data is received via a mobilepositioning system and the position data further comprises position,velocity and acceleration of the mobile information handling system. 16.The information handling system of claim 14, wherein the applicationprocessor determines the trajectory estimation during the future timeinterval based on application of a linear mean square estimator toestimate of a probability of future locations in the trajectoryestimation using current position, velocity and acceleration of themobile information handling system.
 17. The information handling systemof claim 14, wherein the application processor further correlates thetrajectory estimation with the wireless device usage trend data byassessing a frequency of recorded visits to a location in the wirelessdevice usage trend data.
 18. The information handling system of claim14, wherein the application processor further correlates the trajectoryestimation with the wireless device usage trend data by modifying thetrajectory estimation locations to include frequently visited locationswithin one grid square from the trajectory estimation on a location map.19. The information handling system of claim 14, wherein the applicationprocessor selects the future mobile information handling system locationfrom among several probable future mobile information handling systemlocations along the trajectory estimation based on a highest degree ofcorrelation between the trajectory estimation locations and a previouslyvisited location.
 20. The information handling system of claim 17,wherein the mobile information handling system hosts an application forselecting the predicted future mobile information handling systemlocation.